Enabling All In-Edge Deep Learning: A Literature Review
Author:
Affiliation:
1. Computer Science Department, Munster Technological University, Cork, Ireland
2. CSIRO Data61, Marsfield, NSW, Australia
Funder
ADVANCE CRT Ph.D. Cohort
ADAPT SFI Research Centre at Munster Technological University
Science Foundation Ireland through the SFI Research Centres Programme
European Regional Development Fund
Horizon 2020 projects STOP Obesity Platform
ITFLOWS
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/10005208/10007810.pdf?arnumber=10007810
Reference287 articles.
1. AI-Enabled Secure Microservices in Edge Computing: Opportunities and Challenges
2. Unleashing the Tiger: Inference Attacks on Split Learning
3. Distributed DRL-based Resource Allocation for Multicast D2D Communications
4. EdgeKeeper: a trusted edge computing framework for ubiquitous power Internet of Things
5. CryptGPU: Fast Privacy-Preserving Machine Learning on the GPU
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